Predicting the current and future distribution of three Coptis herbs in China under climate change conditions, using the MaxEnt model and chemical analysis

Potential distribution of Blumea balsamifera in China using MaxEnt and the ex situ conservation based on its effective components and fresh leaf yield

Blumea balsamifera is a famous Chinese Minority Medicine, which has a long history in Miao, Li, Zhuang, and other minority areas. In recent years, due to the influence of natural and human factors, the distribution area of B. balsamifera resources has a decreasing trend. Therefore, it is very important to analyze the suitability of B. balsamifera in China. Following three climate change scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) under 2050s and 2070s, geographic information technology (GIS) and maximum entropy model (MaxEnt) were used to simulate the ecological suitability of B. balsamifera. The contents of L-borneol and total flavonoids of B. balsamifera in different populations were determined by gas chromatography (GC) and ultraviolet spectrophotometry (UV). The results showed that the key environmental variables affecting the distribution of B. balsamifera were mean temperature of coldest quarter (6.18-26.57 ℃), precipitation of driest quarter (22.46-169.7 mm), annual precipitation (518.36-1845.29 mm), and temperature seasonality (291.31-878.87). Under current climate situation, the highly suitable habitat was mainly located western Guangxi, southern Yunnan, most of Hainan, southwestern Guizhou, southwestern Guangdong, southeastern Fujian, and western Taiwan, with a total area of 24.1 × 10⁴ km². The areas of the moderately and poorly suitable habitats were 27.57 × 10⁴ km² and 42.43 × 10⁴ km², respectively. Under the future climate change scenarios, the areas of the highly, moderately, and poorly suitable habitats of B. balsamifera showed a significant increasing trend, the geometric center of the total suitable habitats of B. balsamifera would move to the northeast. In recent years, the planting area of B. balsamifera has been reduced on a large scale in Guizhou, and its ex situ protection is imperative. By comparison, the content of L-borneol, total flavonoids and fresh leaf yield had no significant difference between Guizhou and Hainan (P > 0.05), which indicated that Hainan is one of the best choice for ex situ protection of B. balsamifera.

Potential geographic distribution of relict plant Pteroceltis tatarinowii in China under climate change scenarios

Pteroceltis tatarinowii (Pteroceltis: Ulmaceae) is a deciduous tree that has a cultivation history of more than 2000 years in China. As an excellent afforestation tree species and rare and endangered tertiary relic plant, P. tatarinowii has high ecological protection value. Due to the forest destruction caused by predatory logging and natural environmental factors, the population of P. tatarinowii in China has decreased significantly. In this study, the potential geographical distribution of P. tatarinowii in China under climate change was predicted using MaxEnt model and ArcGIS based on 223 effective distribution points of P. tatarinowii and 11 environmental variables. The results showed that: (1) the prediction accuracy of MaxEnt model was extremely high, and the areas under curve (AUC) value of the training data was 0.936; The area of the potential suitable habitat area of P. tatarinowii under current climate condition was 180.84×10⁴ km², and mainly located in the central and southeast regions of China. (2) The domain environmental variables affecting the potential geographical distribution of P. tatarinowii were min temperature of coldest month (12.1~22.7°C), isothermality (26.6~35.8), mean diurnal range 6.9~9.3°C and precipitation of wettest month (189.5 ~955.5 mm). (3) In 2050s and 2070s, compared with current (4.19×10⁴ km²), the area of highly suitable habitat will increase by 0.2%-0.3% (RCP2.6) and 1.22%-3.84% (RCP8.5) respectively. while the poorly, moderately and total suitable habitats will decrease. The gravity center of P. tatarinowii showed a trend of migration to higher latitudes and northern regions in the future. These results will provide theoretical basis for cultivation management and resource protection of P. tatarinowii.

Determination of Cultivation Regions and Quality Parameters of Poria cocos by Near-Infrared Spectroscopy and Chemometrics

Poria cocos (PC) is an important fungus with high medicinal and nutritional values. However, the quality of PC is heavily dependent on multiple factors in the cultivation regions. Traditional methods are not able to perform quality evaluation for this fungus in a short time, and a new method is needed for rapid quality assessment. Here, we used near-infrared (NIR) spectroscopy combined with chemometric method to identify the cultivation regions and determine PC chemical compositions. In our study, 138 batches of samples were collected and their cultivation regions were distinguished by combining NIR spectroscopy and random forest method (RFM) with an accuracy as high as 92.59%. In the meantime, we used partial least square regression (PLSR) to build quantitative models and measure the content of water-soluble extract (WSE), ethanol-soluble extract (ASE), polysaccharides (PSC) and the sum of five triterpenoids (SFT). The performance of these models were verified with correlation coefficients (R²_cal and R²_pre) above 0.9 for the four quality parameters and the relative errors (RE) of PSC, WSE, ASE and SFT at 4.055%, 3.821%, 4.344% and 3.744%, respectively. Overall, a new approach was developed and validated which is able to distinguish PC production regions, quantify its chemical contents, and effectively evaluate PC quality.

Socio-Ecological Effects on the Patterns of Non-native Plant Distributions on Hainan Island

Non-native plants spread to recipient areas via natural or human-mediated modes of dispersal, and, if the non-native species are invasive, introduction potentially causes impacts on native plants and local ecosystems as well as economic losses. Therefore, we studied the diversity and distributional patterns of non-native plant species diversity in the tropical island province of Hainan, China and its relationships with environmental and socioeconomic factors by generating a checklist of species and subsequently performing an analysis of phylogenetic diversity. To generate the checklist, we began with the available, relevant literature representing 19 administrative units of Hainan and determined the casual, naturalized, or invasive status of each species by conducting field surveys within 14 administrative units. We found that non-native plants of Hainan comprise 77 casual species, 42 naturalized species, and 63 invasive species. Moreover, we found that non-native plant species had diverse origins from North and South America, Africa, and Asia and that the most common species across administrative areas belong to the plant families Asteraceae and Fabaceae. Moreover, the numbers of non-native species distributed in the areas of Hainan bording the coast arer greater than those within interior areas of the province. Among the coastal areas, Haikou has the highest species richness and, simultaneously, the highest values for significantly, positively correlated predictor variables, population and GDP (R2 = 0.60, P < 0.01; R2 = 0.64, P < 0.01, respectively). In contrast, the landlocked administrative units of Tunchang and Ding’an have the smallest number of non-native species, while their populations are less than a quarter of that of Haikou and their GDP less than one tenth. Among natural environmental variables, we determined that the number of non-native species had the strongest correlation with the minimum temperature in the coldest month, which predicts a smaller number of non-native species. Additionally, non-native species are primarily distributed in urban and rural built-up areas and agricultural areas; areas that are dominated by human activities. Overall, our study provides a working checklist of the non-native plants of Hainan as well as a theoretical framework and reference for the control of invasive plants of the province.

MaxEnt Modeling to Estimate the Impact of Climate Factors on Distribution of Pinus densiflora

Pinus densiflora is an important evergreen coniferous species with both economic and ecological value. It is an endemic species in East Asia. Global climate warming greatly interferes with species survival. This study explored the impact of climate change on the distribution of this species and the relationship between its geographical distribution and climate demand, so as to provide a theoretical basis for the protection of P. densiflora under the background of global warming. This research used 565 valid data points and 19 typical climatic environmental factors distributed in China, Japan, and South Korea. The potential distribution area of P. densiflora in East Asia under the last glacial maximum (LGM), mid-Holocene, the current situation and two scenarios (RCP 2.6 and RCP 8.5) in the future (2050s and 2070s) was simulated by the MaxEnt model. The species distribution model toolbox in ArcGIS software was used to analyze the potential distribution range and change of P. densiflora. The contribution rates, jackknife test and environmental variable response curves were used to assess the importance of key climate factors. The area under the receiver-operating characteristic curve (AUC) was used to evaluate model accuracy. The MaxEnt model had an excellent simulation effect (AUC = 0.982). The forecast showed that the Korean Peninsula and Japan were highly suitable areas for P. densiflora, and the area had little change. Moreover, during the LGM, there was no large-scale retreat to the south, and it was likely to survive in situ in mountain shelters. The results suggested that Japan may be the origin of P. densiflora rather than the Shandong Peninsula of China. The distribution area of P. densiflora in the mid-Holocene and future scenarios was reduced compared with the current distribution, and the reduction of future distribution was greater, indicating that climate warming will have certain negative impacts on the distribution of P. densiflora in the future. The precipitation of the warmest quarter (Bio18), temperature seasonality (Bio4), mean annual temperature (Bio1) and mean temperature of the wettest quarter (Bio8) had the greatest impact on the distribution area of P. densiflora.

Effects of climate change on the distribution of wild Akebia trifoliata

Understanding the impacts and constraints of climate change on the geographical distribution of wild Akebia trifoliata is crucial for its sustainable management and economic development as a medicinal material or fruit. In this study, according to the first-hand information obtained from field investigation, the distribution and response to climate change of A. trifoliata were studied by the MaxEnt model and ArcGIS. The genetic diversity and population structure of 21 natural populations of A. trifoliata were studied by simple sequence repeat (SSR) markers. The results showed that the most important bioclimatic variable limiting the distribution of A. trifoliata was the Mean Temperature of Coldest Quarter (bio11). Under the scenarios SSP1-2.6 and SSP2-4.5, the suitable area of A. trifoliata in the world will remain stable, and the suitable area will increase significantly under the scenarios of SSP3-7.0 and SSP5-8.5. Under the current climate scenario, the suitable growth regions of A. trifoliata in China were 79.9-122.7°E and 21.5-37.5°N. Under the four emission scenarios in the future, the geometric center of the suitable distribution regions of Akebia trifoliata in China will move to the north. The clustering results of 21 populations of A. trifoliata analyzed by SSR markers showed that they had a trend of evolution from south to north.

Predicting potential distribution of Ziziphus spinosa (Bunge) H.H. Hu ex F.H. Chen in China under climate change scenarios

Ziziphus spinosa (Bunge) H.H. Hu ex F.H. Chen is a woody plant species of the family Rhamnaceae (order Rhamnales) that possesses high nutritional and medicinal value. Predicting the effects of climate change on the distribution of Z. spinosa is of great significance for the investigation, protection, and exploitation of this germplasm resource. For this study, optimized maximum entropy models were employed to predict the distribution patterns and changes of its present (1970-2000) and future (2050s, 2070s, and 2090s) potential suitable regions in China under multiple climate scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 & SSP5-8.5). The results revealed that the total area of the present potential suitable region for Z. spinosa is 162.60 × 104 km2, which accounts for 16.94% of China's territory. Within this area, the regions having low, medium, and high suitability were 80.14 × 104 km2, 81.50 × 104 km2, and 0.96 × 104 km2, respectively, with the high suitability regions being distributed primarily in Shanxi, Hebei, and Beijing Provinces. Except for SSP-1-2.6-2070s, SSP-5-8.5-2070s, and SSP-5-8.5-2090s, the suitable areas for Z. spinosa in the future increased to different degrees. Meanwhile, considering the distribution of Z. spinosa during different periods and under different climate scenarios, our study predicted that the low impact areas of Z. spinosa were mainly restricted to Shanxi, Shaanxi, Ningxia, Gansu, Liaoning, Inner Mongolia, and Jilin Provinces. The results of core distributional shifts showed that, except for SSP1-2.6, the center of the potential suitable region of Z. spinosa exhibited a trend of gradually shifting to the northwest.

Assessing the Impact of Climate Change on Potential Distribution of Meconopsis punicea and Its Influence on Ecosystem Services Supply in the Southeastern Margin of Qinghai-Tibet Plateau

Meconopsis punicea is an iconic ornamental and medicinal plant whose natural habitat has degraded under global climate change, posing a serious threat to the future survival of the species. Therefore, it is critical to analyze the influence of climate change on possible distribution of M. punicea for conservation and sustainable utilization of this species. In this study, we used MaxEnt ecological niche modeling to predict the potential distribution of M. punicea under current and future climate scenarios in the southeastern margin region of Qinghai-Tibet Plateau. Model projections under current climate show that 16.8% of the study area is suitable habitat for Meconopsis. However, future projections indicate a sharp decline in potential habitat for 2050 and 2070 climate change scenarios. Soil type was the most important environmental variable in determining the habitat suitability of M. punicea, with 27.75% contribution to model output. Temperature seasonality (16.41%), precipitation of warmest quarter (14.01%), and precipitation of wettest month (13.02%), precipitation seasonality (9.41%) and annual temperature range (9.24%) also made significant contributions to model output. The mean elevation of suitable habitat for distribution of M. punicea is also likely to shift upward in most future climate change scenarios. This study provides vital information for the protection and sustainable use of medicinal species like M. punicea in the context of global environmental change. Our findings can aid in developing rational, broad-scale adaptation strategies for conservation and management for ecosystem services, in light of future climate changes.

Geographical distribution of As-hyperaccumulator Pteris vittata in China: Environmental factors and climate changes

Understanding the distribution of hyperaccumulators helps to implement more efficient phytoremediation strategies of contaminated sites, however, limited information is available. Here, we investigated the geographical distribution of the first-known arsenic-hyperaccumulator Pteris vittata in China and the key factors under two climate change scenarios (SSP 1-2.6 and SSP 5-8.5) at two time points (2030 and 2070). Species distribution model (MaxEnt) was applied to examine P. vittata distribution based on 399 samples from field surveys and existing specimen records. Further, among 23 environmental factors, 11 variables were used in the MaxEnt model, including temperature, precipitation, elevation, soil property, and UV-B radiation. The results show that P. vittata can grow in ~23% of the regions in China. Specifically, it is mainly distributed in 11 provinces of southern China, including Hainan, Guangdong, Guangxi, Yunnan, Guizhou, Hunan, Hubei, Jiangxi, Fujian, Zhejiang, and Jiangsu. Besides, eastern Sichuan, and southern Henan, Shaanxi, and Anhui are suitable for P. vittata growth. Under two climate change scenarios, P. vittata distribution in China would decrease by ~5.76-7.46 × 10⁴ km² in 2030 and ~3.22-4.68 × 10⁴ km² in 2070, with southern Henan and most Jiangsu being unsuitable for P. vittata growth. Among the 11 environmental variables, the minimum temperature of coldest month (bio6) and temperature annual range (bio7) are the two key factors limiting P. vittata distribution. At bio6 <-5 °C and/or bio7 >33 °C, the regions are unsuitable for P. vittata growth. Based on the MaxEnt model, precipitation had limited effects, so P. vittata can probably survive under both dry and moist environments. This study helps guide phytoremediation of As-polluted soils using P. vittata and provides an example to evaluate habitat suitability of hyperaccumulators at international scales.

Effects of Climate Change on the Distribution of Akebia quinata

Akebia quinata, also known as chocolate vine, is a creeping woody vine which is used as Chinese herbal medicine, and found widely distributed in East Asia. At present, its wild resources are being constantly destroyed. This study aims to provide a theoretical basis for the resource protection of this plant species by analyzing the possible changes in its geographic distribution pattern and its response to climate factors. It is the first time maximum entropy modeling (MaxEnt) and ArcGIS software have been used to predict the distribution of A. quinata in the past, the present, and the future (four greenhouse gas emission scenarios, namely, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Through the prediction results, the impact of climate change on the distribution of A. quinata and the response of A. quinata to climate factors were analyzed. The results showed that the most significant climatic factor affecting the distribution pattern of A. quinata was the annual precipitation. At present, the suitable distribution regions of A. quinata are mainly in the temperate zone, and a few suitable distribution regions are in the tropical zone. The medium and high suitable regions are mainly located in East Asia, accounting for 51.1 and 81.7% of the worldwide medium and high suitable regions, respectively. The migration of the geometric center of the distribution regions of A. quinata in East Asia is mainly affected by the change of distribution regions in China, and the average migration rate of the geometric center in each climate scenario is positively correlated with the level of greenhouse gas emission scenario.

Species Distribution Models of the Spartina alterniflora Loisel in Its Origin and Invasive Country Reveal an Ecological Niche Shift

Spartina alterniflora is a perennial herb native to the American Atlantic coast and is the dominant plant in coastal intertidal wetlands. Since its introduction to China in 1979, it has quickly spread along the coast and has caused various hazards. To control the further spread of S. alterniflora in China, we first reconstructed the history of the spread of S. alterniflora in its invasion and origin countries. We found that S. alterniflora spreads from the central coast to both sides of the coast in China, while it spreads from the west coast to the east coast in America. Furthermore, by comparing 19 environmental variables of S. alterniflora in its invasion and origin countries, it was found that S. alterniflora is more and more adaptable to the high temperature and dry environment in the invasion country. Finally, we predicted the suitable areas for this species in China and America using the maximum entropy (MaxEnt) model and ArcGIS. Overall, through analysis on the dynamic and trend of environmental characteristics during the invasion of S. alterniflora and predicting its suitable area in the invasion area, it guides preventing its reintroduction and preventing its further spread of the species has been found. It has reference significance for studying other similar alien plants and essential enlightening relevance to its invasion and spread in similar areas.

Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model

Hylomecon japonica is considered a natural medicinal plant with anti-inflammatory, anticancer and antibacterial activity. The assessment of climate change impact on its habitat suitability is important for the wild cultivation and standardized planting of H. japonica. In this study, the maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the current and future distribution of H. japonica species, and the contributions of variables were evaluated by using the jackknife test. The area under the receiver operating characteristic curve (AUC) value confirmed the accuracy of the model prediction based on 102 occurrence records. The predicted potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi, Chongqing, Henan, Heilongjiang and other provinces (adaptability index > 0.6). The jackknife experiment showed that the precipitation of driest month (40.5%), mean annual temperature (12.4%), the precipitation of wettest quarter (11.6%) and the subclass of soil (9.7%) were the most important factors affecting the potential distribution of H. japonica. In the future, only under the shared socioeconomic Pathway 245 (SSP 245) scenario model in 2061–2080, the suitable habitat area for H. japonica is expected to show a significant upward trend. The area under other scenarios may not increase or decrease significantly.

Global distribution of soapberries (Sapindus L.) habitats under current and future climate scenarios

Sapindus (Sapindus L.) is a widely distributed economically important tree genus that provides biodiesel, biomedical and biochemical products. However, with climate change, deforestation, and economic development, the diversity of Sapindus germplasms may face the risk of destruction. Therefore, utilising historical environmental data and future climate projections from the BCC-CSM2-MR global climate database, we simulated the current and future global distributions of suitable habitats for Sapindus using a Maximum Entropy (MaxEnt) model. The estimated ecological thresholds for critical environmental factors were: a minimum temperature of 0-20 °C in the coldest month, soil moisture levels of 40-140 mm, a mean temperature of 2-25 °C in the driest quarter, a mean temperature of 19-28 °C in the wettest quarter, and a soil pH of 5.6-7.6. The total suitable habitat area was 6059.97 × 10⁴ km², which was unevenly distributed across six continents. As greenhouse gas emissions increased over time, the area of suitable habitats contracted in lower latitudes and expanded in higher latitudes. Consequently, surveys and conservation should be prioritised in southern hemisphere areas which are in danger of becoming unsuitable. In contrast, other areas in northern and central America, China, and India can be used for conservation and large-scale cultivation in the future.

Potential geographical distribution and environmental explanations of rare and endangered plant species through combined modeling: A case study of Northwest Yunnan, China

In recent decades, due to the effect of climate change and the interference of human activities, the species habitat index has fallen by 2%. Studying on the geographical distribution pattern and predicting the potential geographical distribution of species are of great significance for developing scientific and effective biodiversity conservation strategies. Plenty of rare and endangered species that need immediate conservation are distributed in Northwest Yunnan. In this regard, this research is conducted in the purpose of predicting the potential geographical distribution of 25 rare and endangered plant species in Northwest Yunnan and analyzing the explanation capabilities of various environmental factors on the potential geographical distribution patterns of these species. Initially, the ecological niche model MaxEnt was employed to predict the potential geographical distribution of target species. Following that, the superposition method was applied to obtain the potential geographical distribution pattern of species richness on the spatial scale of the ecological niche model with a resolution of 0.05° × 0.05°. Ultimately, geographically weighted regression (GWR) model was adopted to investigate the explanation capabilities of various environmental parameters on the potential distribution patterns. The research results showed that the average value of the area under the receiver operating curve (AUC) of each species was between 0.80 and 1.00, which indicated that the simulation accuracy of the MaxEnt model for each species was good or excellent. On the whole, the potential distribution area for each species was relatively concentrated and mainly distributed in the central-western, central-eastern and northern regions of Northwest Yunnan. In addition, the potential distribution areas of these species were between 826.33 km2 and 44,963.53 km2. In addition, the annual precipitation (Bio12), precipitation of coldest quarter (Bio19), and population density (Pop) made a greater contribution to the species distribution model, and their contribution values were 25.92%, 15.86%, and 17.95%, respectively. Moreover, the goodness-of-fit R 2 and AIC value of the water model were 0.88 and 7,703.82, respectively, which indicated the water factor largely influenced the potential distribution of these species. These results would contribute to a more comprehensive understanding of the potential geographical distribution pattern and the distribution of suitable habitats of some rare and endangered plant species in Northwest Yunnan and would be helpful for implementing long-term conservation and reintroduction for these species.

Anthropogenic factors are stronger drivers of patterns of endemic plant diversity on Hainan Island of China than natural environmental factors

The roles of natural and anthropogenic factors in contributing to the organization of biodiversity at large and small scales have long been challenging to disentangle, and doing so has never been attempted for the island province of Hainan in China based on patterns of taxonomic and phylogenetic diversity. Therefore, in this study, we evaluated the taxonomic and phylogenetic diversity of endemic plants on the island as a function of anthropogenic and natural variables based on non-metric multi-dimensional scaling (NMDS) ordination and generated generalized linear models (GLMs). We found that the highest phylogenetic diversity (1006) and the lowest mean phylogenetic distance (515.5) was in the provincial capital, Haikou. The NMDS analyses indicated that taxonomic diversity was significantly correlated with industrial revenue (p = 0.006) and population (p = 0.004). Furthermore, most phylogenetic diversity indices were strongly correlated with population and agricultural revenue, while the sampled natural environmental variables were not significantly correlated with plant diversity indices. These findings indicate that anthropogenic factors are the main present-day driving forces of plant diversity in Hainan, though we did detect a significant latitudinal diversity gradient of richness that likely reflects the historical roles of natural environmental factors in the organization of biodiversity on the island. Overall, our results are alarming for biodiversity of the island and indicate that conservation and sustainable use of endemic plant species must be made a critical priority.

Scientometric Analysis of Medicinal and Edible Plant Coptis

Objective: A scientometric analysis to obtain knowledge mapping of Coptis revealed the current research situation, knowledge base and research hotspots in Coptis research.

Methods:Coptis-related documents published from 1987 to 2020 were selected through the Web of Science Core Collection. CiteSpace, VOSviewer and Microsoft Excel were used to construct knowledge maps of the Coptis research field.

Results: A total of 367 documents and their references were analyzed. These papers were primarily published in mainland China (214), followed by Japan (57) and South Korea (52), and they each formed respective cooperation networks. The document co-citation analysis suggested that the identification of Coptis Salisb. species, the production of alkaloids, and the mechanisms of action of these alkaloids formed the knowledge bases in this field. A keyword analysis further revealed that the research hotspots were primarily concentrated in three fields of research involving berberine, Coptis chinensis Franch, and Coptis japonica (Thunb) Makino. Oxidative stress, rat plasma (for the determination of plasma alkaloid contents), and Alzheimer’s disease are recent research hotspots associated with Coptis.

Conclusion:Coptis research was mainly distributed in three countries: China, Japan, and South Korea. Researchers were concerned with the identification of Coptis species, the production of Coptis alkaloids, and the efficacy and pharmacological mechanism of the constituent alkaloids. In addition, the anti-oxidative stress, pharmacokinetics, and Alzheimer’s disease treatment of Coptis are new hotspots in this field. This study provides a reference for Coptis researchers.

Predicting the Potential Geographic Distribution and Habitat Suitability of Two Economic Forest Trees on the Loess Plateau, China

The Loess Plateau is one of the most fragile ecosystems in the world. In order to increase the biodiversity in the area, develop sustainable agriculture and increase the income of the local people, we simulated the potential geographic distribution of two economic forest trees (Malus pumila Mill and Prunus armeniaca L.) in the present and future under two climate scenarios, using the maximum entropy model. In this study, the importance and contributions of environmental variables, areas of suitable habitats, changes in habitat suitability, the direction and distance of habitat range shifts, the change ratios for habitat area and land use proportions, were measured. According to our results, bioclimatic variables, topographic variables and soil variables play a significant role in defining the distribution of M. pumila and P. armeniaca. The min temperature of coldest month (bio6) was the most important environmental variable for the distribution of the two economic forest trees. The second most important factors for M. pumila and P. armeniaca were, respectively, the elevation and precipitation of the driest quarter (bio17). At the time of the study, the area of above moderately suitable habitats (AMSH) was 8.7967 × 104 km2 and 11.4631 × 104 km2 for M. pumila and P. armeniaca. The effect of Shared Socioeconomic Pathway (SSP) 5-85 was more dramatic than that of SSP1-26. Between now and the 2090s (SSP 5-85), the AMSH area of M. pumila is expected to decrease to 7.5957 × 104 km2, while that of P. armeniaca will increase to 34.6465 × 104 km2. The suitability of M. pumila decreased dramatically in the south and southeast regions of the Loess Plateau, increased in the middle and west and resulted in a shift in distance in the range of 78.61~190.63 km to the northwest, while P. armeniaca shifted to the northwest by 64.77~139.85 km. This study provides information for future policymaking regarding economic forest trees in the Loess Plateau.

Past, present, and future geographic range of the relict Mediterranean and Macaronesian Juniperus phoenicea complex

AIM

The aim of this study is to model the past, current, and future distribution of J. phoenicea s.s., J. turbinata, and J. canariensis, based on bioclimatic variables using a maximum entropy model (Maxent) in the Mediterranean and Macaronesian regions.

LOCATION

Mediterranean and Macaronesian.

TAXON

Cupressaceae, Juniperus.

METHODS

Data on the occurrence of the J. phoenicea complex were obtained from the Global Biodiversity Information Facility (GBIF.org), the literature, herbaria, and the authors' field notes. Bioclimatic variables were obtained from the WorldClim database and Paleoclim. The climate data related to species localities were used for predictions of niches by implementation of Maxent, and the model was evaluated with ENMeval.

RESULTS

The potential niches of Juniperus phoenicea during the Last Interglacial period (LIG), Last Glacial Maximum climate (LGM), and Mid-Holocene (MH) covered 30%, 10%, and almost 100%, respectively, of the current potential niche. Climate warming may reduce potential niches by 30% in RCP2.6 and by 90% in RCP8.5. The potential niches of Juniperus turbinata had a broad circum-Mediterranean and Canarian distribution during the LIG and the MH; its distribution extended during the LGM when it was found in more areas than at present. The predicted warming in scenarios RCP2.6 and RCP8.5 could reduce the current potential niche by 30% and 50%, respectively. The model did not find suitable niches for J. canariensis during the LIG and the LGM, but during the MH its potential niche was 30% larger than at present. The climate warming scenario RCP2.6 indicates a reduction in the potential niche by 30%, while RCP8.5 so indicates a reduction of almost 60%.

MAIN CONCLUSIONS

This research can provide information for increasing the protection of the juniper forest and for counteracting the phenomenon of local extinctions caused by anthropic pressure and climate changes.

Maximum Entropy Modeling to Predict the Impact of Climate Change on Pine Wilt Disease in China

Pine wilt disease is a devastating forest disease caused by the pinewood nematode Bursaphelenchus xylophilus, which has been listed as the object of quarantine in China. Climate change influences species and may exacerbate the risk of forest diseases, such as the pine wilt disease. The maximum entropy (MaxEnt) model was used in this study to identify the current and potential distribution and habitat suitability of three pine species and B. xylophilus in China. Further, the potential distribution was modeled using the current (1970-2000) and the projected (2050 and 2070) climate data based on two representative concentration pathways (RCP 2.6 and RCP 8.5), and fairly robust prediction results were obtained. Our model identified that the area south of the Yangtze River in China was the most severely affected place by pine wilt disease, and the eastern foothills of the Tibetan Plateau acted as a geographical barrier to pest distribution. Bioclimatic variables related to temperature influenced pine trees' distribution, while those related to precipitation affected B. xylophilus's distribution. In the future, the suitable area of B. xylophilus will continue to increase; the shifts in the center of gravity of the suitable habitats of the three pine species and B. xylophilus will be different under climate change. The area ideal for pine trees will migrate slightly northward under RCP 8.5. The pine species will continue to face B. xylophilus threat in 2050 and 2070 under the two distinct climate change scenarios. Therefore, we should plan appropriate measures to prevent its expansion. Predicting the distribution of pine species and the impact of climate change on forest diseases is critical for controlling the pests according to local conditions. Thus, the MaxEnt model proposed in this study can be potentially used to forecast the species distribution and disease risks and provide guidance for the timely prevention and management of B. xylophilus.

Modelling the Effects of Climate Change on the Distribution of Endangered Cypripedium japonicum in China

Cypripedium japonicum is an endangered terrestrial orchid species with high ornamental and medicinal value. As global warming continues to intensify, the survival of C. japonicum will be further challenged. Understanding the impact of climate change on its potential distribution is of great significance to conserve this species. In this study, we established an ensemble species distribution model based on occurrence records of C. japonicum and 13 environmental variables to predict its potential distribution under current and future climatic conditions. The results show that the true skill statistic (TSS), Cohen’s kappa statistic (Kappa), and the area under the receiver operating characteristic curve (AUC) values of the ensemble model were 0.968, 0.906, and 0.995, respectively, providing more robust predictions. The key environmental variables affecting the distribution of C. japonicum were the precipitation in the warmest quarter (Bio18) and the mean temperature in the driest quarter (Bio9). Under future climatic conditions, the total suitable habitat of C. japonicum will increase slightly and tend to migrate northwestward, but the highly suitable areas will be severely lost. By 2070, the loss of its highly suitable habitat area will reach 57.69–72.24% under representative concentration pathway (RCP) 4.5 and 8.5 respectively, and the highly suitable habitats in Zhejiang and Anhui will almost disappear. It is noteworthy that the highly suitable habitat of C. japonicum has never crossed the Qinba mountainous area during the migration process of the suitable habitat to the northwest. Meanwhile, as the best-preserved area of highly suitable habitat for C. japonicum in the future, the Qinba mountainous area is of great significance to protect the wild germplasm resources of C. japonicum. In addition, we found that most of the changes predicted for 2070 will already be seen in 2050; the problem of climate change may be more urgent than it is believed.

Chinese caterpillar fungus (Ophiocordyceps sinensis) in China: Current distribution, trading, and futures under climate change and overexploitation

Chinese caterpillar fungus (Ophiocordyceps sinensis) is a precious traditional medicine which is mostly distributed on the Qinghai-Tibetan Plateau (QTP). Due to its medicinal values, it has become one of the most valuable biological commodities and widely traded in recent years worldwide. However, its habitat has changed profoundly in recent years under global warming as well as anthropogenic pressures, resulting in a sharp decline in its wild population in recent years. Based on the occurrence samples, this paper estimates the potential distribution of caterpillar fungus using MaxEnt model. The model simulates potential geographical distribution of the species under current climate conditions, and examine future distributions under different climatic change scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 have been modelled in 2050s and 2070s, respectively). For examining the impacts of climate change in future, the integrated effects of climatic impact, trading, and overexploitation had been analyzed in detailed routes. The results show that: 1) The distribution patterns of caterpillar fungus under scenario RCP 2.6 have been predicted without obvious changes. However, range shift has been observed with significant shrinks across all classes of suitable areas in Tianshan, Kunlun Mountains, and the southwestern QTP in 2050s and 2070s under RCP 4.5, RCP 6.0 and RCP 8.5 scenarios, respectively. 2) The exports were decreasing drastically in recent years. Guangzhou and Hongkong are two international super import and consumption centres of caterpillar fungus in the world. 3) Both ecological and economic sustainable utilization of the caterpillar fungus has been threatened by the combined pressures of climate change and overexploitation. A strict but effective regulation and protection system, even a systematic management plan not just on the collectors but the whole explore process are urgently needed and has to be issued in the QTP.

Current Situation, Global Potential Distribution and Evolution of Six Almond Species in China

Almond resources are widely distributed in Central Asia; its distribution has not been studied in detail. Based on the first-hand data of field investigation, climate variables and chloroplast genome data, climatic characteristics of six almond species in China were analyzed, and the global distribution and evolutionary relationship were predicted. The six almond species are concentrated between 27.99°N and 60.47°N. Different almond species have different climatic characteristics. The climate of the almond species distribution has its characteristics, and the distribution of almond species was consistent with the fatty acid cluster analysis. All the test AUC (area under curve) values of MaxEnt model were larger than 0.92. The seven continents except for Antarctica contain suitable areas for the six almond species, and such areas account for approximately 8.08% of the total area of these six continents. Based on the analysis of chloroplast DNA and the distribution characteristics, the evolutionary relationship of the six almond species was proposed, which indicated that China was not the origin of almond. In this study, the construction of a phylogenetic tree based on the chloroplast genome and the characteristics of geographical distribution were constructed. The six almond species in China may have evolved from "Unknown almond species" through two routes. The MaxEnt model for each almond species provided satisfactory results. The prediction results can provide the important reference for Prunus dulcis cultivation, wild almond species development and protection.

The Relict Ecosystem of Maytenus senegalensis subsp. europaea in an Agricultural Landscape: Past, Present and Future Scenarios

Maytenus senegalensis subsp. europaea is a shrub belonging to the Celastraceae family, whose only European populations are distributed discontinuously along the south-eastern coast of the Iberian Peninsula, forming plant communities with great ecological value, unique in Europe. As it is an endangered species that makes up plant communities with great palaeoecological significance, the development of species distribution models is of major interest under different climatic scenarios, past, present and future, based on the fact that the climate could play a relevant role in the distribution of this species, as well as in the conformation of the communities in which it is integrated. Palaeoecological models were generated for the Maximum Interglacial, Last Maximum Glacial and Middle Holocene periods. The results obtained showed that the widest distribution of this species, and the maximum suitability of its habitat, occurred during the Last Glacial Maximum, when the temperatures of the peninsular southeast were not as contrasting as those of the rest of the European continent and were favored by higher rainfall. Under these conditions, large territories could act as shelters during the glacial period, a hypothesis reflected in the model’s results for this period, which exhibit a further expansion of M. europaea’s ecological niche. The future projection of models in around 2070, for four Representative Concentration Pathways according to the fifth report of the Intergovernmental Panel on Climate Change, showed that the most favorable areas for this species would be Campo de Dalías (southern portion of Almería province) as it presents the bioclimatic characteristics of greater adjustment to M. europaea’s ecological niche model. Currently, some of the largest specimens of the species survive in the agricultural landscapes in the southern Spain. These areas are almost totally destroyed and heavily altered by intensive agriculture greenhouses, also causing a severe fragmentation of the habitat, which implies a prospective extinction scenario in the near future.

Mapping the potential of mangrove forest restoration based on species distribution models: A case study in China

Mangrove forests support numerous ecosystem services and contribute to coastal ecological risk reduction. However, they are one of the most severely threatened ecosystems in the world. China has carried out national mangrove restoration projects, but there is still insufficient scientific information for the strategic planning of this restoration. In this study, we carried out mangrove suitability assessments using the genetic algorithm for rule-set prediction (GARP) and maximum entropy (MaxEnt) models, and we mapped the restoration potential of mangrove forests in China for the first time. The restoration potential index (RPI), which combines suitability and land use data, is proposed as a rapid estimator method for locating theoretically available areas for restoration. The results showed that the MaxEnt model performed better than GARP in predicting potential mangrove distributions. Temperature was the most important environmental factor for determining large scale distribution of mangroves. The predicted northern limit of mangrove distribution was around 28°27' N-28°35' N. Using the RPI approach, 16,800 ha with the potential to restore mangrove forests was identified. According to both models, the largest area with restoration potential occurs along the Guangdong and Guangxi coast. Nationwide, about 75% of the potential area suitable for mangrove forests has been lost as a consequence of land use and is no longer available for restoration. Around 6400 ha of ponds is currently used for aquaculture, accounting for 38% of theoretically restorable areas. These areas can be a priority for mangrove forest restoration. In conclusion, our findings provide a better scientific understanding of mangrove distribution in China and can underpin strategic design and planning of mangrove restoration.

Overexpression of a novel E3 ubiquitin ligase gene from Coptis chinensis Franch enhances drought tolerance in transgenic tobacco

Drought stress has a significant effect on the growth, physiology and biochemistry of medicinal plants. SDIR1 (Salt- and Drought-Induced Ring Finger1), a C3H2C3-type RING-finger E3 ubiquitin ligase gene plays an important role in the stress response of various plants. However, the role of this gene is not clear in Coptis chinensis. In this study, the CcSDIR1 gene was cloned from C. chinensis using RACE and RT-PCR. Sequence analysis revealed that CcSDIR1 had an open reading frame of 840 bp that encodes 279 amino acids with a theoretical molecular weight about 31 kDa and pI value of 5.65 and shared conserved domains with other plants. On comparison with the wild-type plants, overexpression of CcSDIR1 in transgenic tobaccos increased drought tolerance and showed better growth performance. However, lower malondialdehyde contents and high antioxidant enzyme activities were observed in transgenic tobacco plants compared to wild-type plants. In addition, Evans blue staining showed high cell viability of transgenic lines under drought stress. These results suggest that CcSDIR1 regulates various responses to drought stress by increasing antioxidant enzyme activities and reducing oxidative damage. From the study results, the CcSDIR1 gene will be very useful for drought stress research in plants.

Prediction of the Suitable Area of the Chinese White Pines (Pinus subsect. Strobus) under Climate Changes and Implications for Their Conservation

White pines (Pinus subsect. Strobus) play important roles in forest ecosystems in the Northern Hemisphere. Species of this group are narrowly distributed or endangered in China. In this study, we used a species distribution model (SDM) to project and predict the distribution patterns of the 12 species of Chinese white pine under a variety of paleoclimatic and future climate change scenarios based on 39 high-resolution environmental variables and 1459 distribution records. We also computed the centroid shift, range expansion/contraction, and suitability change of the current distribution area to assess the potential risk to each species in the future. The modeling results revealed that the suitable habitat of each species is consistent with but slightly larger than its actual distribution range and that temperature, precipitation, and UV radiation are important determining factors for the distribution of different white pine species. The results indicate that the Last Glacial Maximum (LGM) greatly affected the current distribution of the Chinese white pine species. Additionally, it was predicted that under the future climate change scenarios, there will be a reduction in the area of habitats suitable for P. armandii, P. morrisonicola, and P. mastersiana. Furthermore, some of the current distribution sites of P. armandii, P. kwangtungensis, P. mastersiana, P. morrisonicola, P. sibirica, and P. wallichiana were predicted to become more unsuitable under these scenarios. These results indicate that some Chinese white pine species, such as P. armandii, P. morrisonicola, and P. mastersiana, may have a very high risk of population shrinkage in the future. Overall, this study provided relevant data for the long-term conservation (both in situ and ex situ) and sustainable management of Chinese white pine species.

Wetlands rise and fall: Six endangered wetland species showed different patterns of habitat shift under future climate change

Degradation and loss of species' suitable habitats in response to global warming are well documented, which are assumed to be affected by increasing temperature. Conversely, habitat increase of species is little reported and is often considered anomalous and unrelated to climate change. In this study, we first revealed the climate-change-driven habitat shifts of six endangered wetland plants - Bruguiera gymnorrhiza, Carex doniana, Glyptostrobus pensilis, Leersia hexandra, Metasequoia glyptostroboides, and Pedicularis longiflora. The current and future potential habitats of the six species in China were predicted using a maximum entropy model based on thirty-year occurrence records and climate monitoring (from 1960 to 1990). Furthermore, we observed the change of real habitats of the six species based on eight-year field observations (from 2011 to 2019). We found that the six species exhibited three different patterns of habitat shifts including decrease, unstable, and increase. The analysis on the main decisive environmental factors showed that these patterns of habitat shifts are counter to what would be expected global warming but are mostly determined by precipitation-related environmental factors rather than temperature. Collectively, our findings highlight the importance of combining multiple environmental factors including temperature and precipitation for understanding plant responses to climate change.

Predicting the Suitable Geographical Distribution of Sinadoxa Corydalifolia under Different Climate Change Scenarios in the Three-River Region Using the MaxEnt Model

Sinadoxa corydalifolia is a perennial grass with considerable academic value as a rare species owing to habitat destruction and a narrow distribution. However, its distribution remains unclear. In this study, we predicted the distribution of Sinadoxa corydalifolia in the three-river region (the source of the Yangtze River, Yellow River, and Lancang River) under the context of climate change using the maximum entropy (MaxEnt) model. Under the current climate scenario, the suitable distribution mainly occurred in Yushu County and Nangqian County. The suitable distribution area of Sinadoxa corydalifolia covered 3107 km², accounting for 0.57% of the three-river region. The mean diurnal air temperature range (Bio2), temperature seasonality (Bio4), and mean air temperature of the driest quarter (Bio9) contributed the most to the distribution model for Sinadoxa corydalifolia, with a cumulative contribution of 81.4%. The highest suitability occurred when air temperature seasonality (Bio4) ranged from 6500 to 6900. The highest suitable mean air temperature of the driest quarter ranged from -5 to 0 °C. The highest suitable mean diurnal temperature (Bio2) ranged from 8.9 to 9.7 °C. In future (2041-2060) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: representative concentration pathway (RCP)26 (6171 km²) > RCP45 (6017 km²) > RCP80 (4238 km²) > RCP60 (2505 km²). In future (2061-2080) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: RCP26 (18,299 km²) > RCP60 (11,977 km²) > RCP45 (10,354 km²) > RCP80 (7539 km²). In general, the suitable distribution will increase in the future. The distribution area of Sinadoxa corydalifolia will generally be larger under low CO₂ concentrations than under high CO₂ concentrations. This study will facilitate the development of appropriate conservation measures for Sinadoxa corydalifolia in the three-river region.

Predictive modelling of the distribution of Clematis sect. Fruticella s. str. under climate change reveals a range expansion during the Last Glacial Maximum

Background

The knowledge of distributional dynamics of living organisms is a prerequisite for protecting biodiversity and for the sustainable use of biotic resources. Clematis sect. Fruticella s. str. is a small group of shrubby, yellow-flowered species distributed mainly in arid and semi-arid areas of China. Plants in this section are both horticulturally and ecologically important.

Methods

Using past, present, and future environmental variables and data with Maximum Entropy (Maxent) modeling, we evaluated the importance of the environmental variables on the section's estimated distributions, thus simulating its distributional dynamics over time. The contractions and expansions of suitable habitat between the past and future scenarios and the present were then compared.

Results and Discussion

The models revealed that the areas with high and moderate suitability currently encompass about 725,110 km². The distribution centroid location varies between points in Ningxia and Inner Mongolia during the different scenarios. Elevation, Mean UV-B of Lowest Month, Precipitation of Coldest Quarter, and Mean Temperature of Driest Quarter were major factors determining the section's distribution. Our modeling indicated that Clematis sect. Fruticella underwent a significant range contraction during the last interglacial period, and then expanded during the last glacial maximum (LGM) to amounts like those of the present. Cold, dry, and relatively stable climate, as well as steppe or desert steppe environments may have facilitated range expansion of this cold-adapted, drought-resistant plant taxon during the LGM. Predicted future scenarios show little change in the amounts of suitable habitat for Clematis sect. Fruticella. This study aids understanding of the distributional dynamics of Clematis sect. Fruticella, and the results will help the conservation and sustainable use of these important woody plants in Chinese arid and semiarid areas.